16 research outputs found
Real-time PCR assay to detect the novel Clade Ib monkeypox virus, September 2023 to May 2024
Monkeypox virus (MPXV) is an emerging zoonotic pathogen with complex epidemiology necessitating rapid diagnosis and distinguishing between clades and subclades. The emerging Clade Ib lacks the genomic region used in the Clade I-specific assay from the Centers for Disease Control and Prevention. We report an MPXV real-time PCR to specifically detect Clade Ib. The assay demonstrated proficient sensitivity and specificity in 92 samples and can be included along other TaqMan-based assays to detect MPXV and distinguish between clades and subclades.</p
Evaluating the effectiveness of lockdowns and restrictions during SARS-CoV-2 variant waves in the Canadian province of Nova Scotia
IntroductionAfter the initial onset of the SARS-CoV-2 pandemic, the government of Canada and provincial health authorities imposed restrictive policies to limit virus transmission and mitigate disease burden. In this study, the pandemic implications in the Canadian province of Nova Scotia (NS) were evaluated as a function of the movement of people and governmental restrictions during successive SARS-CoV-2 variant waves (i.e., Alpha through Omicron).MethodsPublicly available data obtained from community mobility reports (Google), the Bank of Canada Stringency Index, the “COVID-19 Tracker” service, including cases, hospitalizations, deaths, and vaccines, population mobility trends, and governmental response data were used to relate the effectiveness of policies in controlling movement and containing multiple waves of SARS-CoV-2.ResultsOur results indicate that the SARS-CoV-2 pandemic inflicted low burden in NS in the initial 2 years of the pandemic. In this period, we identified reduced mobility patterns in the population. We also observed a negative correlation between public transport (−0.78), workplace (−0.69), retail and recreation (−0.68) and governmental restrictions, indicating a tight governmental control of these movement patterns. During the initial 2 years, governmental restrictions were high and the movement of people low, characterizing a ‘seek-and-destroy’ approach. Following this phase, the highly transmissible Omicron (B.1.1.529) variant began circulating in NS at the end of the second year, leading to increased cases, hospitalizations, and deaths. During this Omicron period, unsustainable governmental restrictions and waning public adherence led to increased population mobility, despite increased transmissibility (26.41-fold increase) and lethality (9.62-fold increase) of the novel variant.DiscussionThese findings suggest that the low initial burden caused by the SARS-CoV-2 pandemic was likely a result of enhanced restrictions to contain the movement of people and consequently, the spread of the disease. Easing public health restrictions (as measured by a decline in the BOC index) during periods of high transmissibility of circulating COVID-19 variants contributed to community spread, despite high levels of immunization in NS
Ongoing mpox outbreak in Kamituga, South Kivu province, associated with monkeypox virus of a novel Clade I sub-lineage, Democratic Republic of the Congo, 2024
Since the beginning of 2023, the number of people with suspected monkeypox virus (MPXV) infection have sharply increased in the Democratic Republic of the Congo (DRC). We report near-to-complete MPXV genome sequences derived from six cases from the South Kivu province. Phylogenetic analyses reveal that the MPXV affecting the cases belongs to a novel Clade I sub-lineage. The outbreak strain genome lacks the target sequence of the probe and primers of a commonly used Clade I-specific real-time PCR.</p
A pooled testing strategy for identifying SARS-CoV-2 at low prevalence
Suppressing infections of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) will probably require the rapid identification and isolation of individuals infected with the virus on an ongoing basis. Reverse-transcription polymerase chain reaction (RT-PCR) tests are accurate but costly, which makes the regular testing of every individual expensive. These costs are a challenge for all countries around the world, but particularly for low-to-middle-income countries. Cost reductions can be achieved by pooling (or combining) subsamples and testing them in groups1-7. A balance must be struck between increasing the group size and retaining test sensitivity, as sample dilution increases the likelihood of false-negative test results for individuals with a low viral load in the sampled region at the time of the test8. Similarly, minimizing the number of tests to reduce costs must be balanced against minimizing the time that testing takes, to reduce the spread of the infection. Here we propose an algorithm for pooling subsamples based on the geometry of a hypercube that, at low prevalence, accurately identifies individuals infected with SARS-CoV-2 in a small number of tests and few rounds of testing. We discuss the optimal group size and explain why, given the highly infectious nature of the disease, largely parallel searches are preferred. We report proof-of-concept experiments in which a positive subsample was detected even when diluted 100-fold with negative subsamples (compared with 30-48-fold dilutions described in previous studies9-11). We quantify the loss of sensitivity due to dilution and discuss how it may be mitigated by the frequent re-testing of groups, for example. With the use of these methods, the cost of mass testing could be reduced by a large factor. At low prevalence, the costs decrease in rough proportion to the prevalence. Field trials of our approach are under way in Rwanda and South Africa. The use of group testing on a massive scale to monitor infection rates closely and continually in a population, along with the rapid and effective isolation of people with SARS-CoV-2 infections, provides a promising pathway towards the long-term control of coronavirus disease 2019 (COVID-19).info:eu-repo/semantics/publishe
[Accepted Manuscript] Risk of active tuberculosis among people with diabetes mellitus: systematic review and meta-analysis.
To assess the risk of active TB in people with DM and the factors associated with this risk.
Systematic review and meta-analysis. We searched the literature for studies that reported the effect of DM on TB controlled for the effect of age. Studies that had not established the diagnosis of DM prior to detecting active TB were excluded. Study quality was assessed by Newcastle-Ottawa scale and we conducted a meta-analysis using random-effects models.
14 studies (8 cohort and 6 case-control studies) that involved 22,616,623 participants met the selection criteria and were included in the analysis. There was substantial variation between studies in the estimates of the effect of DM on TB. However, the pooled estimates from 7 high-quality studies showed that diabetic people have a 1.5-fold increased risk of developing active TB versus those without DM (95%CI 1.28-1.76), with relatively small heterogeneity (I2 44%). The increased risk of TB was observed predominantly among DM populations with poor glycaemic control.
There is evidence suggesting an increased risk of developing TB among people with DM, and that improving glycaemic control in DM patients would reduce the risk of developing TB. An integrated approach is needed to control the dual burden of DM and TB. This article is protected by copyright. All rights reserved
Bioscience data literacy at the interface of the environment, human and wildlife : one health-centred education, research and practice perspectives in Rwanda
Advances in information technology have led to the availability of state-of-the-art technologies which in turn have been enabling the generation of unprecedented amounts of complex, structured or unstructured data sets that are sometimes difficult to process using conventional techniques. In particular, handling these large scale data in terms of collection, and aggregation, synthesis and analysis, interpretation, reporting, sharing and archiving processes, and interpreting them into descriptive models and enable effective interpretation requires continued development of robust computational models, algorithms and interoperable analytical frameworks (Hampton et al. 2017). This also involves the vital availability of data management expertise and reflects an imperative need for data science professionals, especially in the context of generating the most informative data for use and drive evidence-based decisions. Considering this, Rwanda has been fueling its economic transformation agenda, and, while this solely depends on natural resources exploitation, the scenario has led to critically concerning anthropogenic threats and unprecedented environmental vulnerability. Acknowledging the urgency to achieve its development needs while at the same time safeguarding the environmental sustainability, Rwanda has been promoting technology-enabled systems and approaches for sustainable management of environment and natural resources.
Learning from global initiatives, Rwanda's journey targets the effective use of technology-supported systems and data science expertise to effectively drive management and decision making needs in environmental management, health research systems and biodiversity conservation planning (Karame et al. 2017). Rwanda champions the adoption and effective use of technology towards delivering its vision of knowledge-based economy. A particular emphasis relates to streamlining the education, research and application of technology-supported systems and platforms and strengthening their effective use. From a practical One Health perspective, Rwanda has been bridging inter-sectoral gaps related to joint planning and resource sharing for informed decision processes. This One Health concept emphasizes the interconnection of the health of human, animals and ecosystems and involves the applications of multidisciplinary, coordinated, cross-sectoral collaborative efforts to attain optimal health for people, animals and the environment (Buttke et al. 2015). One Health constitutes a promising approach in the advancement of biosciences. For example, big data and ecological and digital epidemiology analysis has led to promising progress beyond the traditional transdisciplinary conservation medicine approach, and One Health is now driving solutions to major conservation and health challenges.
This paper aims to explore the perspectives of solving challenges in handling heterogeneous data and sources of uncertainty, the progress and feasibility of adopting (or developing, adapting and customizing) open code- and data-sharing platforms, and integrating the application of flexible statistical models and cloud-computing, all within the confines of limited resources. Africa needs to engage in data science to build and sustain capacity and to effectively use acquired knowledge and skills. Further, Africa can strategically align and tailor existing technology data science platforms to the unique context of this continent. It is time to assess the boundaries, explore new horizons, and reach beyond the limits of current practice in order to enable researchers to get the most from generated data. We envision a long-term integrative and digital approach to handling and processing health, environment, and wildlife data to mark the beginning of our journey forward
Understanding knowledge, attitudes and practices on Ebola Virus Disease: a multi-site mixed methods survey on preparedness in Rwanda
Abstract Background The overall goal of this survey was to understand the knowledge, attitudes, and practices related to the Ebola Virus Disease (EVD) in Rwanda. Methods This mixed-method cross-sectional survey was conducted in five selected districts of Rwanda. Quantitative data were collected from 1,010 participants using Kobo Collect Software and the analysis was performed using SPSS and Python software. Qualitative data were specifically collected from 98 participants through Key Informant Interviews (KIIs) and Focus Group Discussion (FGDs). Interview transcripts were imported into NVIVO 8 for coding and subsequent analysis. Results As per our quantitative findings, we report that from the 1,010 respondents, 99.6% reported having previously heard of Ebola, 97.2% believed that vaccination is important in combatting the disease and 93.3% of individuals reported a willingness to receive vaccination should one become available. Around 54% of the respondents were correct in identifying that the disease is of a viral origin which originates from wild animals (42.1%). When asked if they believed that Rwanda is at risk of an EVD outbreak, 90% of the respondents believe that the country is at risk of an EVD outbreak, and the cofactors *gender* and *whether people dwell in Rubavu/Rusizi* were found to significantly impact their perception of threat. As per our qualitative findings, the respondents mentioned that both geographical proximity and relations with the Democratic Republic of Congo place Rwanda at risk of developing an internal outbreak. Although the respondents seemed to be aware of the Ebola prevention behaviours, it was noted that some of them will require significant time before reintegrating into the community an EVD survivor, as they will first need assurance that the patient has fully recovered. Therefore, the qualitative findings reinforce what we originally reported in the quantitative approach to this study. Conclusion Our results show that there was high EVD-related knowledge and awareness among the general population in Rwanda. However, for strong public health awareness, preparedness, and protection, a massive investment should always be made in education about EVD with a special focus on districts neighboring countries where the disease is consistently being reported
OC 8526 THE RWANDA CLINICAL RESEARCH NETWORK (RWANDA-CRN): A MODEL FOR MIXED SOUTH-SOUTH AND NORTH-SOUTH COLLABORATIONS FOR CLINICAL RESEARCH CAPACITY DEVELOPMENT
BackgroundPoor countries carry 90% of the global burden of disease, with access to only 10% of globally available health research funding and technical capacity. Fragile south–south collaborations hinder effective use of limited resources, career opportunities and funding to retain the insufficiently available quality scientists. The Rwanda Health System established a clinical research network involving academia, non-governmental organisations and private sector to accelerate generation of talented scientists, create enabling environment and incentives to retain scientists by establishing a local funding model.MethodsBased on a baseline assessment, potential clinical trial units were mapped and developed through adoption of a Clinical trial management training model from European Universities. The Rwandan law on Public Private Partnership was leveraged to attract and engage local and international private players in a win-win approach. So far, countries such as Kenya and Sweden were engaged in the roadmap.ResultsFrom 2014 to date, a total of 285 scientists are trained on various clinical research components: Good Clinical Practice (28%), Research Grant writing (14%), systematic review and meta-analysis (9%) and scientific communication (8.7%). Ten Clinical Research Units and one centre for evidence-based healthcare were established. So far 13 health investigator-initiated projects in malaria, metabolic disorders and maternal health were funded through the local funding model. A process to empower six malaria sentinel sites into fully functioning clinical research sites is underway.ConclusionThe creation of strong networks of excellence forclinical research among southern academic, research institutions and pharmaceutical and non-pharmaceutical industry is a promising strategic approach to promote sustainable clinical research capacity. The government vision is that beyond national boundaries, resource sharing and involvement of private players are key factors to mitigate the high burden of disease, nationally and regionally.</jats:sec